publications by categories in reversed chronological order. generated by jekyll-scholar.


  1. 2023_Doumeche_N_arxiv_ceapinns.png
    Convergence and error analysis of PINNs
    Nathan Doumèche, Gérard Biau, and Claire Boyer
    arXiv, 2023
  2. 2023_Jiang_R_p-neurips_tnopimca.png
    Training neural operators to preserve invariant measures of chaotic attractors
    Ruoxi Jiang, Peter Y Lu, Elena Orlova, and 1 more author
    In Advances in Neural Information Processing Systems (NeurIPS), 2023
  3. 2023_Mondal_A_arxiv_koopman.png
    Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
    Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar, and 2 more authors
    arXiv, 2023



    1. 2021_Mclenny_L_w-aaai-mlps_sapinns.png
      Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
      L. McClenny, and U. Braga-Neto
      In AAAI Symposium on Combining Artificial Intelligence and Machine Learning with Physics Sciences, 2021


    1. 2020_Jiang_C_p-meshfreeflownet.png
      MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework
      Chiyu Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, and 6 more authors
      In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, 2020
    2. 2020_Sun_Y_p-msml_neupde.png
      NeuPDE: Neural network based ordinary and partial differential equations for modeling time-dependent data
      Yifan Sun, Linan Zhang, and Hayden Schaeffer
      In Mathematical and Scientific Machine Learning, 2020


    1. 2019_Raissi_M_j-cp_pinns.png
      Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
      M. Raissi, P. Perdikaris, and G.E. Karniadakis
      Journal of Computational Physics, 2019